Public Access
markusro
f9d8de7697
- raise instead of silent None for unsupported operands and empty negation - validate before acquiring lock in Accumulation operators (no RLock leak) - Accumulation._copy_provenance helper, ADC_Result._copy_metadata for all result paths - shared _sandbox_stdout_redirect contextmanager for sandboxed scripts - TemperatureMonitor dead code removal (gtk helper, traceback, unused properties) - new unit tests incl. lock-freedom regression test - gitignore sphinx generated doc/_autosummary/ and doc/damaris/
387 lines
14 KiB
Python
387 lines
14 KiB
Python
import os
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import subprocess
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import threading
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import unittest
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from datetime import datetime
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import numpy as np
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from damaris.data.ADC_Result import ADC_Result
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from damaris.data.Accumulation import Accumulation
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class TestAccumulation(unittest.TestCase):
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@staticmethod
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def create_adc_result():
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x = np.array([0.0, 1.0, 2.0])
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y = [np.array([10, 20, 30]), np.array([15, 25, 35])]
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index = [(0, 1)]
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job_date = datetime(2023, 1, 1)
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desc = {"key": "value"}
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sampl_freq = 1000.0
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job_id = 11
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adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
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adc.set_nChannels(2)
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return adc
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def test_constructor_with_no_arguments(self):
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"""Test initializer with no arguments."""
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accu = Accumulation()
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self.assertFalse(accu.contains_data())
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self.assertEqual(accu.sampling_rate, 0)
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self.assertEqual(len(accu.index), 0)
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self.assertEqual(len(accu.x), 0)
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self.assertEqual(len(accu.y), 0)
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def test_constructor_with_arguments(self):
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"""Test initializer with all arguments."""
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x = np.array([0.0, 1.0, 2.0])
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y = [np.array([10, 20, 30]), np.array([15, 25, 35])]
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n = 1
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index = [(0, 2)]
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sampl_freq = 1000.0
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accu = Accumulation(x=x,
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y=y,
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y_2=None,
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index=index,
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sampl_freq=sampl_freq,
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n=n)
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self.assertTrue(accu.contains_data())
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self.assertEqual(accu.sampling_rate, sampl_freq)
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self.assertEqual(accu.x.all(), x.all())
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self.assertEqual(accu.y[0].all(), y[0].all())
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# TODO make testing strict with array types!
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np.testing.assert_array_equal(accu.x, np.array(x, dtype="float32"), strict=False)
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np.testing.assert_array_equal(accu.y[0], np.array(y[0], dtype="int16"), strict=False)
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np.testing.assert_array_equal(accu.y[1], np.array(y[1], dtype="int16"), strict=False)
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def test_add_adc_result(self):
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"""Test adding sample space."""
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adc = self.create_adc_result()
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accu = Accumulation()
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accu += adc
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self.assertEqual(len(adc.x), len(accu.x))
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self.assertEqual(len(adc.y[0]), len(accu.y[0]))
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self.assertEqual(adc.index[-1], accu.index[-1])
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np.testing.assert_array_equal(accu.x, adc.x)
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np.testing.assert_array_equal(accu.y[0], adc.y[0])
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def test_add_accumulation(self):
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"""Test adding sample space."""
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adc1 = self.create_adc_result()
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adc1.set_description("common", "somerandomtext")
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adc1.set_description("same_variable", "somerandomtext_variable1")
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adc1.set_description("variable1", "somerandomtext_variable1_1")
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adc2 = self.create_adc_result()
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adc2.set_description("common", "somerandomtext")
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adc2.set_description("same_variable", "somerandomtext_variable2")
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adc2.set_description("variable2", "somerandomtext_variable2_2")
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accu1 = Accumulation()
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accu1 += adc1
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print(accu1.common_descriptions)
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accu2 = Accumulation()
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accu2 += adc2
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accu2 += accu1
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self.assertEqual(len(accu1.x), len(accu2.x))
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self.assertEqual(len(accu1.y[0]), len(accu2.y[0]))
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self.assertEqual(accu1.index[-1], accu2.index[-1])
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self.assertEqual(accu1.common_descriptions["same_variable"], "somerandomtext_variable1")
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self.assertEqual(accu2.common_descriptions["common"], "somerandomtext")
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np.testing.assert_array_equal(accu2.x, accu1.x)
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np.testing.assert_array_equal(accu2.y[0], accu1.y[0]*2)
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def test_get_accu_by_index(self):
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"""Test retrieving data by index."""
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accu = Accumulation()
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adc = self.create_adc_result()
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adc.index = [(0, 1), (1, 2)]
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adc.job_id = 42
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accu += adc
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sub_result = accu.get_accu_by_index(1)
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self.assertEqual(sub_result.sampling_rate, 1000.0)
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self.assertTrue(np.array_equal(sub_result.x, np.array([1.0, 2.0])))
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self.assertTrue(np.array_equal(sub_result.y[0], np.array([20, 30])))
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self.assertTrue(np.array_equal(sub_result.y[1], np.array([25, 35])))
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self.assertEqual(sub_result.index, [(0, 1)])
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self.assertEqual(sub_result.common_descriptions, {"key": "value"})
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def test_get_accu_by_index_copies_is_clipped(self):
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"""Test that get_accu_by_index properly copies is_clipped."""
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adc = self.create_adc_result()
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adc.index = [(0, 1), (1, 2)]
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accu = Accumulation()
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accu += adc
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accu.is_clipped = True
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sub_result = accu.get_accu_by_index(1)
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self.assertEqual(sub_result.is_clipped, True)
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def test_get_accu_by_index_data_independence(self):
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"""Test that get_accu_by_index returns independent data (not shared views)."""
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adc = self.create_adc_result()
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adc.index = [(0, 1), (1, 2)]
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accu = Accumulation()
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accu += adc
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original_y0 = accu.y[0].copy()
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sub_result = accu.get_accu_by_index(1)
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sub_result.y[0][0] = 9999
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sub_result.x[0] = 999.0
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self.assertEqual(sub_result.y[0][0], 9999)
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self.assertTrue(np.array_equal(accu.y[0], original_y0))
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# x array should also be independent
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self.assertEqual(accu.x[1], 1.0)
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def test_write_to_csv_without_error(self):
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"""Test the functionality of writing to CSV."""
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from io import StringIO
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x = np.array([0.0, 1.0])
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y = [np.array([10, 20]), np.array([15, 25])]
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index = [(0, 1)]
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job_date = datetime(2023, 1, 1)
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desc = {"key": "value"}
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sampl_freq = 1000.0
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job_id=9
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adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
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accu = Accumulation()
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accu += adc
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output = StringIO()
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accu.write_to_csv(output, delimiter=",")
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content = output.getvalue()
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expected = (
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"# accumulation 1\n"
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"# key : value\n"
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"# t ch0_mean ch1_mean\n"
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"0.000000e+00,1.000000e+01,1.500000e+01\n"
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"1.000000e+00,2.000000e+01,2.500000e+01\n"
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)
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self.assertEqual(content, expected)
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def test_write_to_csv_with_error(self):
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"""Test the functionality of writing to CSV."""
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from io import StringIO
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x = np.array([0.0, 1.0])
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y = [np.array([10, 20]), np.array([15, 25])]
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index = [(0, 1)]
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job_date = datetime(2023, 1, 1)
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desc = {"key": "value"}
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sampl_freq = 1000.0
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job_id=9
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adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
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accu = Accumulation(error=True)
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accu += adc
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output = StringIO()
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accu.write_to_csv(output, delimiter=",")
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content = output.getvalue()
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expected = (
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"# accumulation 1\n"
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"# key : value\n"
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"# t ch0_mean ch0_err ch1_mean ch1_err\n"
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"0.000000e+00,1.000000e+01,0.000000e+00,1.500000e+01,0.000000e+00\n"
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"1.000000e+00,2.000000e+01,0.000000e+00,2.500000e+01,0.000000e+00\n"
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)
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self.assertEqual(content, expected)
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def test_write_to_hdf(self):
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"""Test the functionality of writing to HDF."""
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import tables
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# do not change the values here, or you need to recreate the h5dump with new values
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x = np.array([0.0, 1.0])
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y = [np.array([10, 20]), np.array([15, 25])]
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index = [(0, 1)]
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job_date = datetime(2023, 1, 1)
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desc = {"key": "value"}
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sampl_freq = 1000.0
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job_id = 10
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adc = ADC_Result(x, y, index, sampl_freq, desc, job_id, job_date)
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accu = Accumulation()
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accu += adc
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# write out data
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hdffile = tables.open_file("testaccu.hdf5", mode="w")
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accu.write_to_hdf(hdffile, where="/", name="name", title="title", complib="zlib", complevel=3)
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hdffile.close()
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# read back data with h5dump utility (apt-get -y install hdf5-tools)
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h5dump = subprocess.run(["h5dump", "-d", "/name/accu_data", "testaccu.hdf5"], capture_output=True)
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content = h5dump.stdout.decode("utf-8")
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# Use path relative to project root
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test_dir = os.path.dirname(__file__)
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with open(os.path.join(test_dir, "h5dump1_accu.ascii"), "r") as f:
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expected = f.read()
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self.assertEqual(content, expected)
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os.unlink("testaccu.hdf5")
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def test_operator_len(self):
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"""Test the functionality of __len__"""
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adc = self.create_adc_result()
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accu = Accumulation()
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accu += adc
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self.assertEqual(len(accu), 3)
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def test_operator_add_scalar(self):
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"""
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Test the functionality of __add__ and __radd__
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"""
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adc = self.create_adc_result()
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accu = Accumulation()
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accu += adc
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y = adc.y
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# test integer addition
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i]+10, y[i] + 10)
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accu += 10
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] + 10)
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# test float addition
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accu += 10.
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] + 10 + 10.)
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def test_operator_sub_scalar(self):
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"""
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Test the functionality of __sub__ and __rsub__
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"""
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adc = self.create_adc_result()
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y = adc.y
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accu = Accumulation()
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accu += adc
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# test integer subtraction
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accu -= 10
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] - 10)
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# test float subtraction
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accu -= 10.
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] - 10 - 10.)
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def test_operator_mul_scalar(self):
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"""
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Test the functionality of __mul and __rmul__
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"""
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adc = self.create_adc_result()
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y = adc.y
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accu = Accumulation()
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accu += adc
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# test integer multiplication
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accu *= 10
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] * 10)
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# test float multiplication
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accu *= 10.0
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] * 10 * 10.0)
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def test_operator_truediv_scalar(self):
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"""
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Test the functionality of __truediv__ and __itruediv__
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"""
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adc = self.create_adc_result()
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y = adc.y
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accu = Accumulation()
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accu += adc
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i]/10, y[i] / 10)
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accu /= 10
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] / 10)
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def test_operator_floordiv_scalar(self):
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"""
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Test the functionality of __floordiv__ and __ifloordiv__
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"""
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adc = self.create_adc_result()
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y = adc.y
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accu = Accumulation()
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accu += adc
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i]//10, y[i] // 10)
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accu //= 10
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for i in range(adc.get_nChannels()):
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np.testing.assert_array_equal(accu.y[i], y[i] // 10)
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self.assertRaises(ValueError, accu.__floordiv__, 1.0)
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self.assertRaises(ValueError, accu.__ifloordiv__, 1.0)
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def test_add_invalid_operand_raises(self):
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"""accu + bogus must raise ValueError instead of returning None."""
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adc = self.create_adc_result()
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accu = Accumulation()
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accu += adc
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self.assertRaises(ValueError, accu.__add__, "foo")
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self.assertRaises(ValueError, accu.__iadd__, "foo")
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def test_neg_empty_raises(self):
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"""-empty accumulation must raise ValueError."""
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self.assertRaises(ValueError, Accumulation().__neg__)
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def test_add_adc_result_does_not_modify_job_ids(self):
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"""accu + adc must not insert the adc job id into accu.job_ids."""
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accu = Accumulation()
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accu += self.create_adc_result()
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n_before = len(accu.job_ids)
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adc2 = self.create_adc_result()
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adc2.job_id = 12
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r = accu + adc2
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self.assertIn(12, r.job_ids)
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self.assertNotIn(12, accu.job_ids)
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self.assertEqual(len(accu.job_ids), n_before)
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def test_empty_plus_accumulation_copies_data(self):
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"""empty_accu + accu must copy arrays and metadata, not alias them."""
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adc = self.create_adc_result()
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accu = Accumulation()
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accu += adc
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accu.is_clipped = True
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r = Accumulation() + accu
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self.assertIsNot(r.y[0], accu.y[0])
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self.assertIsNot(r.job_ids, accu.job_ids)
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self.assertTrue(r.is_clipped)
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# in-place operation on the result must leave the operand unchanged
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r *= 2
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np.testing.assert_array_equal(accu.y[0], np.array([10, 20, 30], dtype="float32"))
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def test_accumulation_plus_accumulation_keeps_both_job_ids(self):
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"""accu1 + accu2 must keep the provenance of both operands."""
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adc1 = self.create_adc_result()
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adc2 = self.create_adc_result()
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adc2.job_id = 12
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accu1 = Accumulation()
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accu1 += adc1
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accu2 = Accumulation()
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accu2 += adc2
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r = accu1 + accu2
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self.assertEqual(set(r.job_ids.keys()), {11, 12})
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self.assertEqual(set(accu1.job_ids.keys()), {11})
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self.assertEqual(set(accu2.job_ids.keys()), {12})
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def test_empty_error_plus_non_error_raises(self):
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"""error accumulation + non-error accumulation must raise ValueError."""
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accu = Accumulation()
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accu += self.create_adc_result()
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empty_err = Accumulation(error=True)
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self.assertRaises(ValueError, empty_err.__add__, accu)
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free = []
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def check_lock():
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if empty_err.lock.acquire(timeout=1):
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free.append(True)
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empty_err.lock.release()
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t = threading.Thread(target=check_lock)
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t.start()
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t.join(3)
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self.assertTrue(free, "lock leaked after ValueError in __add__")
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if __name__ == "__main__":
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unittest.main()
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